Ophthalmic imaging system with automatic retinal feature detection

ABSTRACT

A method of automatically detecting a retinal feature using an ophthalmic imaging system and automatically providing at least one of an audio, visual, and tactile indication of the detected retinal feature to a user.

BACKGROUND Technical Field

Embodiments disclosed herein are related to ophthalmic imaging systems.More specifically, embodiments described herein relate to automaticallydetecting structural features of the retina, such as retinal breaks,using optical coherence tomography (OCT).

Related Art

Structural defects in a patient's eye can lead to vision loss. Forexample, a retinal break can be a full-thickness defect in theneurosensory retina. A retinal break can be associated withrhegmatogenous retinal detachment, which can induce severe loss ofvision. Moreover, undetected retinal breaks are the most prevalentreason for failure in retinal detachment surgery.

Conventionally, retinal breaks have been detected through careful fundusexamination by a surgeon during a surgical procedure, such asvitreo-retinal surgery. This can involve en face visualization andexamination using a surgical microscope. The conventional approach canbe limited in its ability to detect relatively small retinal breaks.Thus, a surgeon can continue or finish a surgical procedure withoutappreciating the presence and/or position of a retinal break.

Some attempts have been made to increase the visibility of retinalbreaks. For example, a dye-extrusion technique can involve injection oftrypan blue dye into the subretinal space. Such techniques, however, cancomplicate the surgical procedure and are not commonly used.

Optical coherence tomography (OCT) can be a noninvasive, high resolutioncross-sectional imaging modality. Some efforts have been made tovisualize the retina using OCT. However, these efforts have not involvedautomatic detection of retinal breaks.

Accordingly, there remains a need for improved devices, systems, andmethods that improve the ability to automatically detect structuralfeatures of the retina during a surgical procedure by addressing one ormore of the needs discussed above.

SUMMARY

The presented solution fills an unmet medical need with a uniquesolution to provide automatic detection of structural defects of theretina by using OCT images to analyze one or more retinal layers. Asurgeon can be alerted upon detection of a retinal break or otherfeature during a surgical procedure.

Consistent with some embodiments, a method of automatically detecting aretinal feature using an ophthalmic imaging system includes: acquiringan OCT image of a retina; segmenting the OCT image; generating a metricbased on the segmented OCT image; detecting the retinal feature based onthe metric; and providing an indication of the detected retinal featureto a user.

Consistent with some embodiments, an ophthalmic imaging system includes:an OCT system configured to acquire an image of a retina; a computingdevice coupled to the OCT system and configured to segment the image,generate a metric based on the segmented image, and detect a retinalfeature based on the metric; and an audio/visual/tactile device incommunication with the computing device and configured to provide atleast one of an audio, visual, and tactile indication of the detectedretinal feature to a user.

Additional aspects, features, and advantages of the present disclosurewill become apparent from the following detailed description.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a flow diagram illustrating a method of automaticallydetecting a retinal feature using an ophthalmic imaging system.

FIG. 2a is a two-dimensional OCT image of a retina.

FIG. 2b is a three-dimensional OCT image of a retina.

FIG. 3a is a two-dimensional OCT image of a retina.

FIG. 3b is a three-dimensional OCT image of a retina.

FIG. 4 is a chart illustrating a thickness profile of a retina.

FIG. 5a is a two-dimensional OCT image of a retina.

FIG. 5b is a fundus image of a retina.

FIG. 5c is a pseudo color map representative of a likelihood of aretinal feature.

FIG. 6 is a diagram illustrating an ophthalmic imaging system.

In the drawings, elements having the same designation have the same orsimilar functions.

DETAILED DESCRIPTION

In the following description specific details are set forth describingcertain embodiments. It will be apparent, however, to one skilled in theart that the disclosed embodiments may be practiced without some or allof these specific details. The specific embodiments presented are meantto be illustrative, but not limiting. One skilled in the art may realizeother material that, although not specifically described herein, iswithin the scope and spirit of this disclosure.

The present disclosure describes devices, systems, and methods forautomatically detecting a retinal feature using quantitative imageanalysis of a retinal OCT image. One or more retinal layers, such as theinner limiting membrane (ILM) and the retinal pigment epithelium (RPE),can be identified when the OCT image is segmented. A metric or retinallayer parameter describing the geometry of one or more retinal layers(e.g., thickness of the neurosensory retina, concavity/convexity of theILM, radius of curvature of the ILM, etc.) can be generated based on thesegmented OCT image. The retinal feature can be detected using themetric or retinal layer parameter. For example, a retinal break can bedetected when the thickness of the neurosensory retina is less than athreshold, when the ILM is concave in the area of the retinal feature,and/or when the radius of curvature of the ILM in the area of theretinal feature is greater than a threshold. An audio, visual, and/ortactile indication can be provided to the surgeon during the surgicalprocedure when the retinal feature is detected.

The devices, systems, and methods of the present disclosure providenumerous advantages, including: (1) reducing the surgeon's burden insearching for retinal defects; (2) reducing surgical procedure failuresby minimizing undetected retinal defects; (3) improving surgicalprocedure outcomes by automatically detecting retinal defects andallowing for those defects to be addressed; and (4) increasing surgicalprocedure efficiency by automatically alerting the surgeon to a detectedretinal defect.

FIG. 1 provides a flow diagram of a method 100 of automaticallydetecting a retinal feature using an ophthalmic imaging system. Themethod 100 can include acquiring an OCT image of a retina (step 102).The method 100 can include segmenting the OCT image (step 104). Themethod 100 can include generating a metric based on the segmented OCTimage (step 106). The method 100 can include detecting the retinalfeature based on the metric (step 108). The method 100 can includeproviding an indication of the detected retinal feature to a user (step110). The steps of method 100 can be performed by one or more componentsof an ophthalmic imaging system (e.g., ophthalmic imaging system 600 ofFIG. 6).

Method 100 can include, at step 102, acquiring an OCT image of theretina. An OCT system (e.g., OCT system 620 of FIG. 6) can acquire dataassociated with the OCT image. The OCT system can include an imagingprobe configured to penetrate a portion of a patient's eye and image theinterior of the patient's eye, including the retina. An external OCTsystem can be configured to image the eye, including the retina, whilepositioned external relative to the patient's eye. A computing device(e.g., computing device 610 of FIG. 6) can process the data acquired bythe OCT system to generate the OCT image.

The OCT system can be configured to split an imaging light received froma light source into an imaging beam that is directed onto targetbiological tissue (e.g., by the imaging probe) and a reference beam thatcan be directed onto a reference mirror. The OCT system can be a Fourierdomain (e.g., spectral domain, swept-source, etc.) or a time domainsystem. The OCT system can be further configured to receive the imaginglight reflected from the target biological tissue (e.g., captured by theimaging probe, the external OCT system, etc.). The interference patternbetween the reflected imaging light and the reference beam is utilizedto generate images of the target biological tissue. Accordingly, the OCTsystem can include a detector configured to detect the interferencepattern. The detector can include Charge-Coupled Detectors (CCDs),pixels, or an array of any other type of sensor(s) that generate anelectric signal based on detected light. Further, the detector caninclude a two-dimensional sensor array and a detector camera.

The OCT image can be two-dimensional or three-dimensional. For example,FIG. 2a provides a two-dimensional OCT image 200 of a portion of theretina, and FIG. 2b provides a three-dimensional OCT image 250 of aportion of the retina. A retinal break 208 can be seen on the right sideof FIGS. 2a and 2b . The retinal break 208 can be automatically detectedusing the systems, methods, and devices described herein. A blood vessel212 can be seen on the left side of FIGS. 2a and 2 b.

Method 100 can include, at step 104, segmenting the OCT image. Thecomputing device can identify one or more retinal layers using the dataassociated with the OCT image. Segmenting the OCT image can includeidentifying an inner limiting membrane (ILM), a nerve fiber layer, aganglion cell layer, an inner plexiform layer, an inner nuclear layer,an outer plexiform layer, an outer nuclear layer, an external limitingmembrane, a layer of rods and cones, a retinal pigment epithelium (RPE),and/or other retinal layer(s). FIG. 3a provides the two-dimensional OCTimage 200 with boundaries of an ILM layer 202 and an RPE layer 204identified. Similarly, FIG. 3b provides the three-dimensional OCT image250 with boundaries of the ILM layer 202 and the RPE layer 204identified.

Method 100 can include, at step 106, generating a metric based on thesegmented OCT image. The metric can be a retinal layer parameter thatobjectively represents a geometry of one or more retinal layers using,for example, one or more numerical values. The retinal layer parametercan be a thickness, an intensity, a phase, a speckle size, a vasculardensity, a size, a concavity/convexity, and/or a radius of curvature ofone or more retinal layers. For example, generating the metric caninclude determining a numerical representation of theconcavity/convexity of the ILM. For example, a radius of curvature ofthe ILM in the area of the retinal feature can be determined. Theretinal layer parameter can be determined using any one, two, three,four, or more retinal layers. Generating the metric can includedetermining a thickness of the neurosensory retina using, for example,the ILM and RPE. The thickness of the neurosensory retina can include adistance between the ILM and RPE. A numerical representation of thethickness can be used as the metric. The retinal layer parameter can bedetermined using one retinal layer and a strip of predefined thicknessthat surrounds the one retinal layer. Two or more metrics can begenerated and utilized to evaluate the retina.

Method 100 can include, at step 108, detecting one or more retinalfeatures based on the generated metric. The detected retinal feature canbe a structural aspect of the retina that is indicative of a defect. Forexample, the retinal feature can be a break, a hole, a tear, a dialysis,a growth, a protrusion, a depression, a region with subretinal fluid,etc. Multiple retinal features and/or types of retinal features can bedetected. The retinal feature(s) can be detected using one or more ofthe metrics. For example, the thickness of the neurosensory retina andthe concavity/convexity of the ILM can be utilized. Utilizing more thanone metric can advantageously increase the certainty of retinal featuredetection.

Detecting the retinal feature can include comparing the retinal layerparameter to the threshold. For example, when the generated metric (step106) includes the thickness of the neurosensory retina, detecting theretinal feature can include comparing the thickness to a thresholdthickness. The retinal feature can be detected when the retinal layerparameter, such as thickness of the neurosensory retina, among others,is greater than or less than the threshold. For example, a retinal breakor a retinal hole can be detected when the thickness is less than thethreshold. On the other hand, a growth or a protrusion of the retina canbe detected when the thickness is greater than the threshold. Thethreshold thickness can be in the range of, for example, 50 microns to300 microns, 75 microns to 300 microns, 100 microns to 250 microns, orother suitable range. Thickness varies along the retina (e.g., at ornear the fovea, peripheral retina, etc.), and the threshold can beselected based on a position along the retina where the retinal featureis located.

Detecting the retinal feature using the generated metric (step 106) caninclude analyzing whether the one or more retinal layers, such as theILM, among others, has a concave or convex shape and/or the degree ofthe concavity/convexity (e.g., the radius of curvature). For example, anILM in the area of the retinal feature that is concave can be indicativeof a retinal break or a retinal hole, whereas an ILM that is convex canbe indicative of a growth or a protrusion in the retina. In that regard,detecting the retinal feature can include comparing a radius ofcurvature of the ILM in the area of the retinal feature to a thresholdradius of curvature indicative of the presence of the retinal feature. Aretinal feature can be detected when the radius of curvature is greaterthan or less than the threshold. For example, a retinal break or aretinal hole can be detected when a concave portion of the ILM has aradius of curvature less than the threshold. The threshold radius ofcurvature for detecting a retinal break can be in the range of, forexample, between about 0.1 mm and about 12 mm, between about 1.0 mm andabout 6 mm, or between about 2.0 mm and about 4.0 mm, including valuessuch as 10 mm, 9 mm, 8 mm, 7 mm, 6 mm, 5 mm, 4 mm, 3 mm, 2 mm, 1 mm, orother suitable value. A combination of the concavity/convexity and thecorresponding radius of curvature can be utilized to detect the retinalfeature.

The threshold(s) used in detecting the retinal feature can be adaptiveor patient-specific. For example, a threshold can be a percentagedifference in the neurosensory retina thickness compared to adjacentareas. Thus, a retinal feature can be detected when an area of thepatient's neurosensory retina has a thickness greater than or less than,e.g., 50% of the thickness of adjacent areas. Similarly, a retinalfeature can be detected when the radius of curvature of the ILM in thearea of the retinal feature is greater than or less than, e.g., 50% ofthe radius of curvature of adjacent areas. The threshold can be between,for example, 1%-100%, 1%-75%, 1%-50%, 1%-25%, etc. The one or morethresholds can be selected based on empirical data. For example, acollection or database of patients can be used to determine a fixed,normal range of neurosensory retina thickness for patients with similarcharacteristics. Thus, a retinal feature can be detected when an area ofthe patient's neurosensory retina has a thickness outside of (e.g.,greater than or less than) the fixed, normal range expected for thepatient. Such empirical data can be used to determine a defaultthreshold value, which may be adjusted based on patient specificcharacteristics. While this discussion specifically mentions thicknessof the neurosensory retina, it is understood that theconcavity/convexity, radius of curvature, and/or other metrics can besimilarly patient-specific or more generally applicable.

FIG. 4 provides a chart 400 that is representative of a thicknessprofile of the neurosensory retina. The data associated with the chart400 can be based on the segmented OCT image. The x-axis of the chart 400can represent the position along the neurosensory retina in units ofpixels. The y-axis can represent the thickness of the neurosensoryretina in units of pixels. A curve 206 can represent the distance of theILM from the RPE along the retina. The neurosensory retina thicknessdepicted in chart 400 can be the metric used to detect the retinal break208. The retinal break 208 can be an area along the neurosensory retinawith a thickness that is significantly different from adjacent areas(e.g., less than 50%) and/or an area with a thickness less than a fixed,normal range. While this discussion specifically mentions thickness ofthe neurosensory retina, it is understood that the concavity/convexity,radius of curvature, and/or other metrics can be similarly used todetect the retinal break or other retinal feature.

Method 100 can include, at step 110, providing an indication of thedetected retinal feature to a user. For example, an audio, visual,and/or tactile indication can be provided using an audio/visual/tactiledevice (e.g., audio/visual/tactile device 630 of FIG. 6). The indicationcan alert the surgeon, during the surgical procedure, as to the presenceand/or position of the detected retinal feature. As shown in FIG. 5a ,an indication 210 of the detected retinal break 208 can be a geometricalobject (e.g., a square, a circle, a polygon, an ellipse, etc.)positioned around the retinal break 208. The indication 210 can beoverlaid on and/or otherwise combined with the OCT image 200, and thecombined OCT image can be output to the audio/visual/tactile device.

As shown in FIG. 5b , the indication 210 can be shaped based on thedetected retinal break 208. As also shown in FIG. 5b , the indication210 can be overlaid on and/or otherwise combined with a fundus image 260of the eye (e.g., instead of the two-dimensional OCT image 200) and thecombined fundus image can be output to the audio/visual/tactile device.

As shown in FIG. 5c , a pseudo color map 270 can be generated based onthe detected retinal break 208. The pseudo color map 270 can berepresentative of the likelihood of the presence of a retinal feature ata given location of the retina. The indication 210 can be an area of thepseudo color map 270 that illustrates a high likelihood of the retinalfeature being positioned in the area. The pseudo color map can be outputto the audio/visual/tactile device.

Generally, the indication 210 can include text, one or more other shapesor symbols, and/or other visual alerts. The indication 210 can bevariously positioned relative to the retinal feature. The indication 210can include an audible signal to alert the user/surgeon to the presenceand/or position of a detected retinal feature. The indication 210 caninclude tactile and/or haptic feedback to the surgeon.

FIG. 6 provides a block diagram of an ophthalmic imaging system 600. Theimaging system 600 can include an OCT system 620 that is configured toacquire an image of the retina. The imaging system 600 can include acomputing device 610 that is configured to segment the image, generate ametric based on the segmented image, and detect a retinal feature basedon evaluation of the generated metric. The computing device 610 and theOCT system 620 can be configured to perform features similar to thosedescribed above. The imaging system 600 can include anaudio/visual/tactile device 630 in communication with the computingdevice 610 and configured to provide at least one of an audio, visual,and tactile indication of the detected retinal feature. Theaudio/visual/tactile device 630 can be a standalone device and/or acomponent that is part of the computing device 610 or the OCT system620. For example, the audio/visual/tactile device 630 can be a displaydevice with integrated speakers.

Embodiments as described herein can provide devices, systems, andmethods that facilitate automatic detection of structural defects in theretina by analyzing retinal OCT images. The devices, systems, andmethods described herein can be used with any imaging modality in whichthe position, geometry, and/or contour of one or more retinal layers canbe identified. The examples provided above are exemplary only and arenot intended to be limiting. One skilled in the art may readily deviseother systems consistent with the disclosed embodiments which areintended to be within the scope of this disclosure. As such, theapplication is limited only by the following claims.

The invention claimed is:
 1. A system, comprising: an optical coherencetomography (OCT) imaging system configured to acquire an OCT image of aretina; a non-transitory computer-readable medium storing instructionsthat, when executed, cause a processor to: segment the OCT image toidentify a neurosensory retina and an inner limiting membrane of theneurosensory retina; generate a plurality of metrics based on thesegmented OCT image, wherein the plurality of metrics includes: athickness of the neurosensory retina in a first area of the retina and asecond area of the retina; and a radius of curvature of the innerlimiting membrane in the first area of the retina and the second area ofthe retina; wherein the first and the second areas of the retina areadjacent; compare the thickness of the neurosensory retina and theradius of curvature of the inner limiting membrane in the first areawith the thickness of the neurosensory retina and the radius ofcurvature of the inner limiting membrane in the second area; determinethat the thickness of the neurosensory retina in the first area differsfrom the thickness of the neurosensory retina in the second area and theradius of curvature of the inner limiting membrane in the first areadiffers from the radius of curvature of the inner limiting membrane inthe second area; based on the determination, indicate a location of aprobable retinal break to a user.
 2. The system of claim 1, furthercomprising: a display; and wherein the non-transitory computer-readablemedium stores instructions that, when executed, cause the processor to:generate a combined image comprising a visual indicator overlaid on theOCT image or a fundus image; and provide the combined image to thedisplay.
 3. The system of claim 1, further comprising: a display; andwherein the non-transitory computer-readable medium stores instructionsthat, when executed, cause the processor to: generate a pseudo color maprepresentative of a probability of the location of the retinal break;and provide the pseudo color map to the display.
 4. The system of claim1, further comprising a tactile device configured to provide tactile orhaptic feedback indicating the location of at least one of the firstarea and the second area based on the tactile indicator generated by theinstructions.
 5. The system of claim 1, wherein the OCT system isconfigured to acquire a three-dimensional OCT image.
 6. A system,comprising: an optical coherence tomography (OCT) imaging systemconfigured to acquire an OCT image of a retina; and a non-transitorycomputer-readable medium storing instructions that, when executed, causea processor to: segment the OCT image to identify a neurosensory retinaand an inner limiting membrane of the neurosensory retina; generate aplurality of metrics based on the segmented OCT image, wherein theplurality of metrics includes: a thickness of the neurosensory retina ina first area of the retina and a second area of the retina; and a radiusof curvature of the inner limiting membrane in the first area of theretina and the second area of the retina; wherein the first and thesecond areas of the retina are adjacent; compare the thickness of theneurosensory retina and the radius of curvature of the inner limitingmembrane in the first area with the thickness of the neurosensory retinaand the radius of curvature of the inner limiting membrane in the secondarea; determine that a difference in the thickness of the neurosensoryretina in the first area and the second area meets or exceeds a firstthreshold and a difference in the radius of curvature of the innerlimiting membrane in the first area and the second area i-s meets orexceeds a second threshold; and based on the determination, indicate alocation of a probable retinal break to a user.
 7. The system of claim6, wherein at least one of the first threshold and the second thresholdis configurable by the user.
 8. The system of claim 6, wherein thenon-transitory computer-readable medium stores instructions that, whenexecuted, cause the processor to adjust at least one of the firstthreshold and the second threshold based on patient-specificcharacteristics.
 9. The system of claim 6, further comprising: adisplay; and wherein the non-transitory computer-readable medium storesinstructions that, when executed, cause the processor to: generate acombined image comprising a visual indicator overlaid on the OCT imageor a fundus image; and provide the combined image to the display. 10.The system of claim 6, further comprising: a display; and wherein thenon-transitory computer-readable medium stores instructions that, whenexecuted, cause the processor to: generate a pseudo color maprepresentative of a probability of the location of the retinal break;and provide the pseudo color map to the display.
 11. The system of claim6, further comprising a tactile device configured to provide tactile orhaptic feedback indicating the location of at least one of the firstarea and the second area based on the tactile indicator generated by theinstructions.
 12. The system of claim 6, wherein the OCT system isconfigured to acquire a three-dimensional OCT image.
 13. A method,comprising: acquiring an OCT image of a retina with an optical coherencetomography (OCT) imaging system of an ophthalmic surgical system;segmenting the OCT image by an image processor of the ophthalmicsurgical system to identify a neurosensory retina and an inner limitingmembrane of the neurosensory retina; generating, by the image processor,the a plurality of metrics based on the segmented OCT image, wherein theplurality of metrics includes: a thickness of the neurosensory retina ina first area of the retina and a second area of the retina; and a radiusof curvature of the inner limiting membrane in the first area of theretina and the second area of the retina; wherein the first and thesecond areas of the retina are adjacent; determining, by the imageprocessor, at least one of the following: the thickness of theneurosensory retina in the first area is less than the thickness of theneurosensory retina in the second area and the radius of curvature ofthe inner limiting membrane in the first area is greater than the radiusof curvature of the inner limiting membrane in the second area; and adifference in the thickness of the neurosensory retina in the first areaand the second area meets or exceeds a first threshold and a differencein the radius of curvature of the inner limiting membrane in the firstarea and the second area meets or exceeds a second threshold; and basedon the determination, providing at least one of an audio, visual, andtactile indicator to indicate a location of a probable retinal break toa user.
 14. The method of claim 13, further comprising: adjusting atleast one of the first threshold and the second threshold based onpatient-specific characteristics.
 15. The method of claim 13, furthercomprising generating, by the ophthalmic surgical system, a combinedimage comprising the visual indicator overlaid on the OCT image or afundus image; and providing the combined image to a display.
 16. Themethod of claim 13, further comprising generating, by the ophthalmicsurgical system, a pseudo color map representative of a probability ofthe location of the retinal break; and providing the pseudo color map toa display.
 17. The method of claim 13, further comprising providingtactile or haptic feedback indicating the location of the probableretinal break.